tangdian commented on a change in pull request #4067: [TE] Holt Winters detector URL: https://github.com/apache/incubator-pinot/pull/4067#discussion_r275872214
########## File path: thirdeye/thirdeye-pinot/src/main/java/org/apache/pinot/thirdeye/detection/components/HoltWintersDetector.java ########## @@ -0,0 +1,541 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ +package org.apache.pinot.thirdeye.detection.components; + +import java.util.ArrayList; +import java.util.Collections; +import java.util.List; +import java.util.concurrent.TimeUnit; +import org.apache.commons.math3.analysis.MultivariateFunction; +import org.apache.commons.math3.optim.PointValuePair; +import org.apache.pinot.thirdeye.common.time.TimeGranularity; +import org.apache.pinot.thirdeye.dataframe.BooleanSeries; +import org.apache.pinot.thirdeye.dataframe.DataFrame; +import org.apache.pinot.thirdeye.dataframe.DoubleSeries; +import org.apache.pinot.thirdeye.dataframe.LongSeries; +import org.apache.pinot.thirdeye.dataframe.Series; +import org.apache.pinot.thirdeye.dataframe.util.MetricSlice; +import org.apache.pinot.thirdeye.datalayer.dto.DatasetConfigDTO; +import org.apache.pinot.thirdeye.datalayer.dto.MergedAnomalyResultDTO; +import org.apache.pinot.thirdeye.detection.ConfigUtils; +import org.apache.pinot.thirdeye.detection.DetectionUtils; +import org.apache.pinot.thirdeye.detection.InputDataFetcher; +import org.apache.pinot.thirdeye.detection.Pattern; +import org.apache.pinot.thirdeye.detection.algorithm.AlgorithmUtils; +import org.apache.pinot.thirdeye.detection.annotation.Components; +import org.apache.pinot.thirdeye.detection.annotation.DetectionTag; +import org.apache.pinot.thirdeye.detection.annotation.Param; +import org.apache.pinot.thirdeye.detection.spec.HoltWintersDetectorSpec; +import org.apache.pinot.thirdeye.detection.spi.components.AnomalyDetector; +import org.apache.pinot.thirdeye.detection.spi.components.BaselineProvider; +import org.apache.pinot.thirdeye.detection.spi.model.InputData; +import org.apache.pinot.thirdeye.detection.spi.model.InputDataSpec; +import org.apache.pinot.thirdeye.detection.spi.model.TimeSeries; +import org.apache.pinot.thirdeye.rootcause.impl.MetricEntity; +import org.joda.time.DateTime; +import org.joda.time.Interval; +import org.joda.time.Period; +import org.apache.commons.math3.optim.MaxIter; +import org.apache.commons.math3.optim.nonlinear.scalar.ObjectiveFunction; +import org.apache.commons.math3.optim.MaxEval; +import org.apache.commons.math3.optim.SimpleBounds; +import org.apache.commons.math3.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer; +import org.apache.commons.math3.optim.InitialGuess; +import org.apache.commons.math3.optim.nonlinear.scalar.GoalType; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; +import static org.apache.pinot.thirdeye.dataframe.util.DataFrameUtils.*; + +/** + * Holt-Winters forecasting algorithm with multiplicative method + * Supports seasonality and trend detection + * https://otexts.com/fpp2/holt-winters.html + */ +@Components(title = "Holt Winters triple exponential smoothing forecasting and detection", + type = "HOLT_WINTERS_RULE", + tags = {DetectionTag.RULE_DETECTION}, + description = "Forecast with holt winters triple exponential smoothing and generate anomalies", + params = { + @Param(name = "alpha"), + @Param(name = "beta"), + @Param(name = "gamma"), + @Param(name = "period"), + @Param(name = "pattern"), + @Param(name = "sensitivity"), + @Param(name = "kernelSmoothing")}) +public class HoltWintersDetector implements BaselineProvider<HoltWintersDetectorSpec>, + AnomalyDetector<HoltWintersDetectorSpec> { + private static final Logger LOG = LoggerFactory.getLogger(HoltWintersDetector.class); + private InputDataFetcher dataFetcher; + private static final String COL_CURR = "current"; + private static final String COL_BASE = "baseline"; + private static final String COL_ANOMALY = "anomaly"; + private static final String COL_PATTERN = "pattern"; + private static final String COL_DIFF = "diff"; + private static final String COL_DIFF_VIOLATION = "diff_violation"; + private static final String COL_ERROR = "error"; + private static final long KERNEL_PERIOD = 3600000L; + private static final int LOOKBACK = 60; + + private int period; + private double alpha; + private double beta; + private double gamma; + private Pattern pattern; + private TimeGranularity timeGranularity; + private double sensitivity; + private String monitoringGranularity; + private boolean smoothing; + private Period lookbackPeriod = ConfigUtils.parsePeriod(LOOKBACK + "DAYS"); + + @Override + public void init(HoltWintersDetectorSpec spec, InputDataFetcher dataFetcher) { + this.period = spec.getPeriod(); + this.alpha = spec.getAlpha(); + this.beta = spec.getBeta(); + this.gamma = spec.getGamma(); + this.dataFetcher = dataFetcher; + this.pattern = spec.getPattern(); + this.smoothing = spec.getSmoothing(); + + this.sensitivity = spec.getSensitivity(); + this.monitoringGranularity = spec.getMonitoringGranularity(); + if (this.monitoringGranularity.equals("1_MONTHS")) { + this.timeGranularity = MetricSlice.NATIVE_GRANULARITY; + } else { + this.timeGranularity = TimeGranularity.fromString(spec.getMonitoringGranularity()); + } + } + + @Override + public TimeSeries computePredictedTimeSeries(MetricSlice slice) { + MetricEntity metricEntity = MetricEntity.fromSlice(slice, 0); Review comment: I checked but the function MetricEntity.fromSlice(slice) does not exist ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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